Shared exposures or management fashions? Antecedents of convergence in the insurance and banking industries

Abstract We study convergence in the attention of decision‐makers across the insurance and banking industries. Our analysis is based on textual risk disclosures (10‐K reports, 2006–2018), providing a snapshot of corporate priorities and contexts. We theoretically link convergence with decision‐making contexts via the Attention‐Based View. Leveraging strategic management theory, we identify antecedents of convergence in attention and, therefore, potentially, risk contagion. These include common trends in the macro‐environment, substitution threats, and management fashions. We combine this theoretical framework with machine learning tools to create quantitative measures of convergence in attention and its antecedents. We find that the proposed measure of convergence is predictive of inter‐ and intra‐industry stock correlations. Finally, based on regression and sensitivity analyses, we identify the relative importance of different antecedents, showing that shared risk management fashions largely drive Inter‐industry convergence in attention. This highlights challenges when interpreting regulatory text data in the context of predicting contagion risk.

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Publication Details

Journal
Journal of Risk & Insurance
Published
2025-08-20
DOI
https://doi.org/10.1111/jori.70013
Primary Topic
Insurance and Financial Risk Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Shared exposures or management fashions? Antecedents of convergence in the insurance and banking industries

Lei Fang, Andreas Tsanakas, Gianvito Lanzolla
Journal of Risk & Insurance
Insurance and Financial Risk Management
article

Shared exposures or management fashions? Antecedents of convergence in the insurance and banking industries

Lei Fang, Andreas Tsanakas, Gianvito Lanzolla
article en

Abstract

Abstract We study convergence in the attention of decision‐makers across the insurance and banking industries. Our analysis is based on textual risk disclosures (10‐K reports, 2006–2018), providing a snapshot of corporate priorities and contexts. We theoretically link convergence with decision‐making contexts via the Attention‐Based View. Leveraging strategic management theory, we identify antecedents of convergence in attention and, therefore, potentially, risk contagion. These include common trends in the macro‐environment, substitution threats, and management fashions. We combine this theoretical framework with machine learning tools to create quantitative measures of convergence in attention and its antecedents. We find that the proposed measure of convergence is predictive of inter‐ and intra‐industry stock correlations. Finally, based on regression and sensitivity analyses, we identify the relative importance of different antecedents, showing that shared risk management fashions largely drive Inter‐industry convergence in attention. This highlights challenges when interpreting regulatory text data in the context of predicting contagion risk.

Journal of Risk & InsuranceVol. 92(3)
St George's, University of London (GB), Queen Mary University of London (GB), City St George's, University of London (GB)
Openalex Percentile: Top 70%
Insurance and Financial Risk Management
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